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Current developments in automotive industry such as hybrid powertrains and the continuously increasing demands on emission control systems, are pushing complexity still further. Validation of such systems lead to a huge amount of test cases and hence extreme testing efforts on the road. At the same time the pressure to reduce costs and minimize development time is creating challenging boundaries on development teams. Therefore, it is of utmost importance to utilize testing and validation prototypes in the most efficient way. It is necessary to apply high levels of instrumentation and collect as much data as possible. And a streamlined data pipeline allows the fleet managers to get new insights from the raw data and control the validation vehicles as well as the development team in the most efficient way. In this paper we will demonstrate a data-driven approach for validation testing.

The current work investigates a method in 1D modeling of cooling systems including discretized cooling package with non-uniform boundary conditions. In a stacked cooling package the heat transfer through each heat exchanger depends on the mass flows and temperature fields. These are a result of complex three-dimensional phenomena, which take place in the under-hood and are highly non-uniform. A typical approach in 1D simulations is to assume these to be uniform, which reduces the authenticity of the simulation and calls for additional calibrations, normally done with input from test measurements. The presented work employs 3D CFD simulations of complete vehicle in STAR-CCM+ to perform a comprehensive study of mass-flow and thermal distribution over the inlet of the cooling package of a Volvo FM commercial vehicle in several steady-state operating points.

An advanced catalytic exhaust after-treatment system addresses the problem of NOX emissions from heavy-duty diesel trucks, relying on real-time catalyst modelling. The system consists of de-NOX catalysts, a device for injection of a reducing agent (diesel fuel) upstream the catalysts, and computer programmes to control the injection of the reducing agent and to model the engine and catalysts in real time. Experiments with 5 different air-assisted injectors were performed to determine the effect of injector design on the distribution of the injected diesel in the exhaust gas stream. A two-injector set-up was investigated to determine whether system efficiency could be increased without increasing the amount of catalyst or the amount of reducing agent necessary for the desired outcome. The results were verified by performing European standard transient cycle tests as well as stationary tests.

The three-way-catalyst (TWC) is an essential part of the exhaust aftertreatment system in spark-ignited powertrains, converting nearly all toxic emissions to harmless gasses. The TWC’s conversion efficiency is significantly temperature-dependent, and cold-starts can be the dominating source of emissions for vehicles with frequent start/stops (e.g. hybrid vehicles). In this paper we develop a thermal TWC model and calibrate it with experimental data. Due to the few number of state variables the model is well suited for fast offline simulation as well as subsequent on-line control, for instance using non-linear state-feedback or explicit MPC. Using the model could allow an on-line controller to more optimally adjust the engine ignition timing, the power in an electric catalyst pre-heater, and/or the power split ratio in a hybrid vehicle when the catalyst is not completely hot.

An engine model for use in computer simulation of transient behavior in drivetrain and vehicle systems is presented. Two elements, important for deviation (e.g. turbo-lag) from steady state characteristics, are the inertia of the supercharging unit (turbo shaft) and the fuel injection control system. No extensive combustion calculations are carried out within the model. Instead it uses condensed results from existing combustion models and measurements. The model is semi-empirical. Some of the engine specific properties needed for simulation are (e.g. for a turbocharged diesel): engine data in steady state operation, mappings of compressor and turbine performance, inertia of the engine components condensed to the crankshaft, turbo shaft inertia, displacement, compression ratio and the essentials of the fuel injection control strategy. Input parameters to the computer program based on the model are accelerator pedal position and external torque acting on the flywheel.

Squeak and rattle (S&R) are nonstationary annoying and unwanted noises in the car cabin that result in considerable warranty costs for car manufacturers. Introduction of cars with remarkably lower background noises and the recent emphasis on electrification and autonomous driving further stress the need for producing squeak- and rattle-free cars. Automotive manufacturers use several road disturbances for physical evaluation and verification of S&R. The excitation signals collected from these road profiles are also employed in subsystem shaker rigs and virtual simulations that are gradually replacing physical complete vehicle test and verification. Considering the need for a shorter lead time and the introduction of optimisation loops, it is necessary to have efficient and inclusive excitation load cases for robust S&R evaluation.

This paper describes a method for optimization of engine settings in view of best total cost of operation fluids. Under specific legal NOX tailpipe emissions requirements the engine out NOX can be matched to the current achievable SCR NOX conversion efficiency. In view of a heavy duty long haul truck application various specific engine operation modes are defined. A heavy duty diesel engine was calibrated for all operation modes in an engine test cell. The characteristics of engine operation are demonstrated in different transient test cycles. Optimum engine operation mode (EOM) selection strategies between individual engine operation modes are discussed in view of legal test cycles and real world driving cycles which have been derived from on-road tests.

Eliminating toxic exhaust emissions, amongst them particulate matter (PM), is one of the driving factors behind the increasing use of electrified vehicles. However, it is frequently overseen that PM arise not only from combustion, but from non-exhaust traffic related causes as well; in particular from the vehicle brakes, tires and the road surface. Furthermore, as electrified vehicles weigh more and typically exhibit higher torques at low speeds, their non-exhaust emissions tend to be higher than for comparable conventional vehicles, especially those generated by tires. Fortunately, tire related emissions are directly related to tire wear, so that limiting tire wear can reduce these emissions as well. This can be accomplished by intelligently modulating the vehicle torque profile in real time, to limit the operation in conditions of higher tire wear.

Existing battery parameter model structures are evaluated by estimating model parameters on real driving data applying standard system identification methods. Models are then evaluated on the test data in terms of goodness of fit and RMSE in voltage predictions. This is different from previous battery model evaluations where a common approach is to train parameters using standardized tests, e.g. hybrid pulse-power capability (HPPC), with predetermined charge and discharge sequences. Equivalent linear circuit models of different complexity were tested and evaluated in order to identify parameter dependencies at different state of charge levels and temperatures. Models are then used to create voltage output given a current, state of charge and temperature. The average accuracy of modelling the DC bus voltage provides a model goodness of fit average higher than 90% for a single RC circuit model.

This paper presents results of a parametric CFD modeling study of a prototype Free Piston Engine (FPE), designed for application in a series hybrid electric vehicle. Since the piston motion is governed by Newton's second law, accounting for the forces acting on the piston/translator, i.e. friction forces, electrical forces, and in-cylinder gas forces, having a high-level control system is vital. The control system changes the electrical force applied during the stroke, thus obtaining the desired compression ratio. Identical control algorithms were implemented in a MATLAB/SIMULINK model to those applied in the prototype engine. The ignition delay and heat release data used in the MATLAB/SIMULINK model are predicted by the KIVA-3V CFD code which incorporates detailed chemical kinetics (305 reactions among 70 species).

Traditional power train development work is concentrated mainly on test bed and on chassis dyno. Though we can simulate a lot of real world conditions on testbed and chassis dyno today, on road application work willis gaining more attention. This means that strategies and tools for invehicle testing under real world conditions are becoming more important. Emission, performance, fuel economy, combustion noise and driving comfort are linked to combustion quality, i.e. quality of fuel mixture preparation and flame propagation. The known testing and research equipment is only partly or not at all applicable for in-vehicle development work. New tools for on the road testing are required. Following, a general view on in-vehicle power train testing will be given. Additionally, new ways to investigate cylinder and cycle specific soot formation in GDI engines with fiber optic tools will be presented.

The transport sector is experiencing a shift to zero-carbon powertrains driven by aggressive international policies aiming to fight climate change. Battery electric vehicles (BEVs) will play the main role in passenger car applications, while diversified solutions are under investigation for the heavy-duty sector. Within this framework, Light Commercial Vehicles (LCVs) impact is not negligible and accountable for about 2.5% of greenhouse gas (GHG) emissions in Europe. In this regard, few LCV comparative assessments on green powertrains are available in the scientific literature and justified by the fact that several factors and limitations should be considered and addressed to define optimal powertrain solutions for specific use cases. The proposed research study deals with a comparative numerical assessment of different zero-carbon powertrain solutions for LCV. BEVs are compared to hydrogen-based fuel cells (FC) and internal combustion engines (ICE) powered vehicles.

A design method for ultra-dependable control-by-wire systems is presented here. With a top-down approach, exploiting the system's intrinsic redundancy combined with a scalable software redundancy, it is possible to meet dependability requirements cost-effectively. The method starts with the system's functions, which are broken down to the basic elements; task, sensor or actuator. A task graph shows the basic elements interrelationships. Sensor and actuator nodes form a non-redundant hardware architecture. The functional task-graph gives input when allocating software on the node architecture. Tasks are allocated to achieve low inter-node communication and transient fault tolerance using scalable software redundancy. Hardware is added to meet the dependability requirements. Finally, the method describes fault handling and bus scheduling. The proposed method has been used in two cases; a fly-by-wire aircraft and a drive-by-wire car.

Battery Electric Vehicles and Extended Range Electric Vehicles, like the Chevrolet Volt, can use electrical energy from the Grid to meet the majority of a driver�s transportation needs. This has the positive societal effects of displace petroleum consumption and associated pollutants from combustion on a well to wheels basis, as well as reduced energy costs for the driver. CO2 may also be lower, but this depends upon the nature of the grid energy generation. There is a mix of sources � coal-fired, gas -fired, nuclear or renewables, like hydro, solar, wind or biomass for grid electrical energy. This mix changes by region, and also on the weather and time of day. By monitoring the grid mix and communicating it to drivers (or to their vehicles) in real-time, electrically driven vehicles may be recharged to take advantage of the lowest CO2, and potentially lower cost charging opportunities.

Real world operating scenarios have a major influence on emissions and fuel consumption. To reduce climate-relevant and environmentally harmful gaseous emissions and the exploitation of fossil resources, deep understanding concerning the real drive behavior of mobile sources is needed because emissions and fuel consumption of e.g. passenger cars, operated in real world conditions, considerably differ from the officially published values which are valid for specific test cycles only [1]. Due to legislative regulations by the European Commission a methodology to measure real drive emissions RDE is well approved for heavy duty vehicles and automotive applications but may not be adapted similar to two-wheeler-applications. This is due to several issues when using the state of the art portable emission measurement system PEMS that will be discussed.

The paper gives an overview of the partially extremely complex problem when looking into commonalities and differences of the three main application areas of engines and powertrains - automotive, agricultural tractors, and industrial engines, the last being predominantly but not exclusively focused on construction equipment. The modern “platform” approach has been used in the automotive world to a large extent and the learned experiences may be of interest for the agricultural tractors and/or the construction equipment manufacturers. On the other hand the truck engine engineers and manufacturers will learn more about the special requirements of the tractor and the industrial engines fields, and thus influence concepts and development procedures and also the production of the automotive engines which in many cases serve as the basis for derivate engines.

Gasoline turbocharged direct injection (GTDI) engines, such as EcoBoost™ from Ford, are becoming established as a high value technology solution to improve passenger car and light truck fuel economy. Due to their high specific performance and excellent low-speed torque, improved fuel economy can be realized due to downsizing and downspeeding without sacrificing performance and driveability while meeting the most stringent future emissions standards with an inexpensive three-way catalyst. A logical and synergistic extension of the EcoBoost™ strategy is the use of E85 (approximately 85% ethanol and 15% gasoline) for knock mitigation. Direct injection of E85 is very effective in suppressing knock due to ethanol's high heat of vaporization - which increases the charge cooling benefit of direct injection - and inherently high octane rating. As a result, higher boost levels can be achieved while maintaining optimal combustion phasing giving high thermal efficiency.

The transition towards battery electric vehicles (BEVs) has increased the focus of vehicle manufacturers on energy efficiency. Ensuring adequate airflow through the heat exchanger is necessary to climatize the vehicle, at the cost of an increase in the aerodynamic drag. With lower cooling airflow requirements in BEVs during driving, the front air intakes could be made smaller and thus be placed with greater freedom. This paper explores the effects on exterior aerodynamics caused by securing a constant cooling airflow through intakes at various positions across the front of the vehicle. High-fidelity simulations were performed on a variation of the open-source AeroSUV model that is more representative of a BEV configuration. To focus on the exterior aerodynamic changes, and under the assumption that the cooling requirements would remain the same for a given driving condition, a constant mass flow boundary condition was defined at the cooling airflow inlets and outlets.

Semi-active suspension systems for ground vehicles have been the focus of research for several years as they offer improvements in vehicle comfort and handling. This kind of suspension has attracted more interest compared to active suspension systems especially due to lower cost and energy consumption. In this paper the capabilities of a semi-active front axle suspension are investigated for a commercial vehicle. A half-truck model of a 4x2 tractor and semitrailer combination is developed in Matlab/Simulink for this purpose. Also, a 2 DOF roll plane model is considered to capture the roll motion of the vehicle body mass. Employing the above-mentioned models, results from on-off and continuous variable semi-active damping systems are compared to the ones from the passive suspension system according to ride comfort and handling safety characteristics.

The drag from the underbody, including wheels and wheel housing, constitutes a significant amount of the total aerodynamic drag of heavy vehicles. A correct simulation of the underbody boundary conditions, including rotating wheels and moving ground, has turned out to be of great importance in the minimising of the aerodynamic drag. In the current study several front wheel housing design parameters have been evaluated using Computational Fluid Dynamics (CFD). Design concepts, like enclosed inner wheel housings, underbody panel and wheel housing ventilation, were evaluated by flow analysis and comparison of the drag force contribution. It was shown that changes to the wheel housing geometry had an important impact on the local flow field and force distribution. The total drag of the vehicle decreased with reduced wheel housing volume and wheel housing ventilation can reduce the aerodynamic drag significantly provided it is designed properly.